Using Quantitative Analysis for Theory Identification

• In Event: Roundtable Session 18
  In Roundtable Session: Exploratory Approaches to Latent Variable Model Building and Theory Development

Abstract

This study used a grounded theory approach to quantitative data analysis for theory identification. Exploratory factor analysis (EFA) and latent class analysis (LCA) were conducted to discover patterns in collectivist data from the World Values Survey 2005. The results from both of these methods argue for a more complex definition of collectivism than traditionally theorized. The EFA showed that the factor structures were not the same across regions even when examining the same variables. The LCA results showed a different number of classes across regions and a multitude of class patterns. Overall, these analyses were used to illustrate the utility of a grounded theory approach to quantitative data analysis and the obscured patterns it uncovers.

Authors

• Hannah Grossman, University of California - Santa Barbara

• Mary E. Brenner, University of California - Santa Barbara

• Karen L. Nylund-Gibson, University of California - Santa Barbara